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  <h1>Series</h1>
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  <h2>Constructor</h2>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.html#pandas.Series" title="pandas.Series">Series</a>([data, index, dtype, name, copy, …])</td>
        <td>One-dimensional ndarray with axis labels (including time series).</td>
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  </table>
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  <h2>Attributes</h2>
  <p><strong>Axes</strong></p>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.index.html#pandas.Series.index" title="pandas.Series.index">Series.index</a></td>
        <td>The index (axis labels) of the Series.</td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.array.html#pandas.Series.array" title="pandas.Series.array">Series.array</a></td>
        <td>The ExtensionArray of the data backing this Series or Index.</td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.values.html#pandas.Series.values" title="pandas.Series.values">Series.values</a></td>
        <td>Return Series as ndarray or ndarray-like depending on the dtype.</td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dtype.html#pandas.Series.dtype" title="pandas.Series.dtype">Series.dtype</a></td>
        <td>Return the dtype object of the underlying data.</td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.ftype.html#pandas.Series.ftype" title="pandas.Series.ftype">Series.ftype</a></td>
        <td>Return if the data is sparse|dense.</td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.shape.html#pandas.Series.shape" title="pandas.Series.shape">Series.shape</a></td>
        <td>Return a tuple of the shape of the underlying data.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.nbytes.html#pandas.Series.nbytes" title="pandas.Series.nbytes">Series.nbytes</a></td>
        <td>Return the number of bytes in the underlying data.</td>
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.ndim.html#pandas.Series.ndim" title="pandas.Series.ndim">Series.ndim</a></td>
        <td>Number of dimensions of the underlying data, by definition 1.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.size.html#pandas.Series.size" title="pandas.Series.size">Series.size</a></td>
        <td>Return the number of elements in the underlying data.</td>
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.strides.html#pandas.Series.strides" title="pandas.Series.strides">Series.strides</a></td>
        <td>Return the strides of the underlying data.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.itemsize.html#pandas.Series.itemsize" title="pandas.Series.itemsize">Series.itemsize</a></td>
        <td>Return the size of the dtype of the item of the underlying data.</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.base.html#pandas.Series.base" title="pandas.Series.base">Series.base</a></td>
        <td>Return the base object if the memory of the underlying data is shared.</td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.T.html#pandas.Series.T" title="pandas.Series.T">Series.T</a></td>
        <td>Return the transpose, which is by definition self.</td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.memory_usage.html#pandas.Series.memory_usage" title="pandas.Series.memory_usage">Series.memory_usage</a>([index, deep])</td>
        <td>Return the memory usage of the Series.</td>
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.hasnans.html#pandas.Series.hasnans" title="pandas.Series.hasnans">Series.hasnans</a></td>
        <td>Return if I have any nans; enables various perf speedups.</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.flags.html#pandas.Series.flags" title="pandas.Series.flags">Series.flags</a></td>
        <td></td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.empty.html#pandas.Series.empty" title="pandas.Series.empty">Series.empty</a></td>
        <td></td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dtypes.html#pandas.Series.dtypes" title="pandas.Series.dtypes">Series.dtypes</a></td>
        <td>Return the dtype object of the underlying data.</td>
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.ftypes.html#pandas.Series.ftypes" title="pandas.Series.ftypes">Series.ftypes</a></td>
        <td>Return if the data is sparse|dense.</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.data.html#pandas.Series.data" title="pandas.Series.data">Series.data</a></td>
        <td>Return the data pointer of the underlying data.</td>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.is_copy.html#pandas.Series.is_copy" title="pandas.Series.is_copy">Series.is_copy</a></td>
        <td>Return the copy.</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.name.html#pandas.Series.name" title="pandas.Series.name">Series.name</a></td>
        <td>Return name of the Series.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.put.html#pandas.Series.put" title="pandas.Series.put">Series.put</a>(*args, **kwargs)</td>
        <td>Applies the put method to its values attribute if it has one.</td>
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  <h2>Conversion</h2>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.astype.html#pandas.Series.astype" title="pandas.Series.astype">Series.astype</a>(dtype[, copy, errors])</td>
        <td>Cast a pandas object to a specified dtype dtype.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.infer_objects.html#pandas.Series.infer_objects" title="pandas.Series.infer_objects">Series.infer_objects</a>()</td>
        <td>Attempt to infer better dtypes for object columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.convert_objects.html#pandas.Series.convert_objects" title="pandas.Series.convert_objects">Series.convert_objects</a>([convert_dates, …])</td>
        <td>(DEPRECATED) Attempt to infer better dtype for object columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.copy.html#pandas.Series.copy" title="pandas.Series.copy">Series.copy</a>([deep])</td>
        <td>Make a copy of this object&rsquo;s indices and data.</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.bool.html#pandas.Series.bool" title="pandas.Series.bool">Series.bool</a>()</td>
        <td>Return the bool of a single element PandasObject.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_numpy.html#pandas.Series.to_numpy" title="pandas.Series.to_numpy">Series.to_numpy</a>([dtype, copy])</td>
        <td>A NumPy ndarray representing the values in this Series or Index.</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_period.html#pandas.Series.to_period" title="pandas.Series.to_period">Series.to_period</a>([freq, copy])</td>
        <td>Convert Series from DatetimeIndex to PeriodIndex with desired frequency (inferred from index if not passed).</td>
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_timestamp.html#pandas.Series.to_timestamp" title="pandas.Series.to_timestamp">Series.to_timestamp</a>([freq, how, copy])</td>
        <td>Cast to datetimeindex of timestamps, at <em>beginning</em> of period.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_list.html#pandas.Series.to_list" title="pandas.Series.to_list">Series.to_list</a>()</td>
        <td>Return a list of the values.</td>
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.get_values.html#pandas.Series.get_values" title="pandas.Series.get_values">Series.get_values</a>()</td>
        <td>Same as values (but handles sparseness conversions); is a view.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.__array__.html#pandas.Series.__array__" title="pandas.Series.__array__">Series.__array__</a>([dtype])</td>
        <td>Return the values as a NumPy array.</td>
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</div>
<div class="w3-container">
  <h2>Indexing, iteration</h2>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.get.html#pandas.Series.get" title="pandas.Series.get">Series.get</a>(key[, default])</td>
        <td>Get item from object for given key (DataFrame column, Panel slice, etc.).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.at.html#pandas.Series.at" title="pandas.Series.at">Series.at</a></td>
        <td>Access a single value for a row/column label pair.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.iat.html#pandas.Series.iat" title="pandas.Series.iat">Series.iat</a></td>
        <td>Access a single value for a row/column pair by integer position.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.loc.html#pandas.Series.loc" title="pandas.Series.loc">Series.loc</a></td>
        <td>Access a group of rows and columns by label(s) or a boolean array.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.iloc.html#pandas.Series.iloc" title="pandas.Series.iloc">Series.iloc</a></td>
        <td>Purely integer-location based indexing for selection by position.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.__iter__.html#pandas.Series.__iter__" title="pandas.Series.__iter__">Series.__iter__</a>()</td>
        <td>Return an iterator of the values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.iteritems.html#pandas.Series.iteritems" title="pandas.Series.iteritems">Series.iteritems</a>()</td>
        <td>Lazily iterate over (index, value) tuples.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.items.html#pandas.Series.items" title="pandas.Series.items">Series.items</a>()</td>
        <td>Lazily iterate over (index, value) tuples.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.keys.html#pandas.Series.keys" title="pandas.Series.keys">Series.keys</a>()</td>
        <td>Alias for index.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.pop.html#pandas.Series.pop" title="pandas.Series.pop">Series.pop</a>(item)</td>
        <td>Return item and drop from frame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.item.html#pandas.Series.item" title="pandas.Series.item">Series.item</a>()</td>
        <td>Return the first element of the underlying data as a python scalar.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.xs.html#pandas.Series.xs" title="pandas.Series.xs">Series.xs</a>(key[, axis, level, drop_level])</td>
        <td>Return cross-section from the Series/DataFrame.</td>
      </tr>
    </tbody>
  </table>
  <p>For more information on .at, .iat, .loc, and .iloc, see the <a href="https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#indexing">indexing documentation</a>.</p>
</div>
<div class="w3-container">
  <h2>Binary operator functions</h2>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.add.html#pandas.Series.add" title="pandas.Series.add">Series.add</a>(other[, level, fill_value, axis])</td>
        <td>Addition of series and other, element-wise (binary operator add).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sub.html#pandas.Series.sub" title="pandas.Series.sub">Series.sub</a>(other[, level, fill_value, axis])</td>
        <td>Subtraction of series and other, element-wise (binary operator sub).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.mul.html#pandas.Series.mul" title="pandas.Series.mul">Series.mul</a>(other[, level, fill_value, axis])</td>
        <td>Multiplication of series and other, element-wise (binary operator mul).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.div.html#pandas.Series.div" title="pandas.Series.div">Series.div</a>(other[, level, fill_value, axis])</td>
        <td>Floating division of series and other, element-wise (binary operator truediv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.truediv.html#pandas.Series.truediv" title="pandas.Series.truediv">Series.truediv</a>(other[, level, fill_value, axis])</td>
        <td>Floating division of series and other, element-wise (binary operator truediv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.floordiv.html#pandas.Series.floordiv" title="pandas.Series.floordiv">Series.floordiv</a>(other[, level, fill_value, axis])</td>
        <td>Integer division of series and other, element-wise (binary operator floordiv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.mod.html#pandas.Series.mod" title="pandas.Series.mod">Series.mod</a>(other[, level, fill_value, axis])</td>
        <td>Modulo of series and other, element-wise (binary operator mod).</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.pow.html#pandas.Series.pow" title="pandas.Series.pow">Series.pow</a>(other[, level, fill_value, axis])</td>
        <td>Exponential power of series and other, element-wise (binary operator pow).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.radd.html#pandas.Series.radd" title="pandas.Series.radd">Series.radd</a>(other[, level, fill_value, axis])</td>
        <td>Addition of series and other, element-wise (binary operator radd).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rsub.html#pandas.Series.rsub" title="pandas.Series.rsub">Series.rsub</a>(other[, level, fill_value, axis])</td>
        <td>Subtraction of series and other, element-wise (binary operator rsub).</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rmul.html#pandas.Series.rmul" title="pandas.Series.rmul">Series.rmul</a>(other[, level, fill_value, axis])</td>
        <td>Multiplication of series and other, element-wise (binary operator rmul).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rdiv.html#pandas.Series.rdiv" title="pandas.Series.rdiv">Series.rdiv</a>(other[, level, fill_value, axis])</td>
        <td>Floating division of series and other, element-wise (binary operator rtruediv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rtruediv.html#pandas.Series.rtruediv" title="pandas.Series.rtruediv">Series.rtruediv</a>(other[, level, fill_value, axis])</td>
        <td>Floating division of series and other, element-wise (binary operator rtruediv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rfloordiv.html#pandas.Series.rfloordiv" title="pandas.Series.rfloordiv">Series.rfloordiv</a>(other[, level, fill_value, …])</td>
        <td>Integer division of series and other, element-wise (binary operator rfloordiv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rmod.html#pandas.Series.rmod" title="pandas.Series.rmod">Series.rmod</a>(other[, level, fill_value, axis])</td>
        <td>Modulo of series and other, element-wise (binary operator rmod).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rpow.html#pandas.Series.rpow" title="pandas.Series.rpow">Series.rpow</a>(other[, level, fill_value, axis])</td>
        <td>Exponential power of series and other, element-wise (binary operator rpow).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.combine.html#pandas.Series.combine" title="pandas.Series.combine">Series.combine</a>(other, func[, fill_value])</td>
        <td>Combine the Series with a Series or scalar according to func.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.combine_first.html#pandas.Series.combine_first" title="pandas.Series.combine_first">Series.combine_first</a>(other)</td>
        <td>Combine Series values, choosing the calling Series&rsquo;s values first.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.round.html#pandas.Series.round" title="pandas.Series.round">Series.round</a>([decimals])</td>
        <td>Round each value in a Series to the given number of decimals.</td>
      </tr>
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        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.lt.html#pandas.Series.lt" title="pandas.Series.lt">Series.lt</a>(other[, level, fill_value, axis])</td>
        <td>Less than of series and other, element-wise (binary operator lt).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.gt.html#pandas.Series.gt" title="pandas.Series.gt">Series.gt</a>(other[, level, fill_value, axis])</td>
        <td>Greater than of series and other, element-wise (binary operator gt).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.le.html#pandas.Series.le" title="pandas.Series.le">Series.le</a>(other[, level, fill_value, axis])</td>
        <td>Less than or equal to of series and other, element-wise (binary operator le).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.ge.html#pandas.Series.ge" title="pandas.Series.ge">Series.ge</a>(other[, level, fill_value, axis])</td>
        <td>Greater than or equal to of series and other, element-wise (binary operator ge).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.ne.html#pandas.Series.ne" title="pandas.Series.ne">Series.ne</a>(other[, level, fill_value, axis])</td>
        <td>Not equal to of series and other, element-wise (binary operator ne).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.eq.html#pandas.Series.eq" title="pandas.Series.eq">Series.eq</a>(other[, level, fill_value, axis])</td>
        <td>Equal to of series and other, element-wise (binary operator eq).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.product.html#pandas.Series.product" title="pandas.Series.product">Series.product</a>([axis, skipna, level, …])</td>
        <td>Return the product of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dot.html#pandas.Series.dot" title="pandas.Series.dot">Series.dot</a>(other)</td>
        <td>Compute the dot product between the Series and the columns of other.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Function application, GroupBy &amp; Window</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.apply.html#pandas.Series.apply" title="pandas.Series.apply">Series.apply</a>(func[, convert_dtype, args])</td>
        <td>Invoke function on values of Series.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.agg.html#pandas.Series.agg" title="pandas.Series.agg">Series.agg</a>(func[, axis])</td>
        <td>Aggregate using one or more operations over the specified axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.aggregate.html#pandas.Series.aggregate" title="pandas.Series.aggregate">Series.aggregate</a>(func[, axis])</td>
        <td>Aggregate using one or more operations over the specified axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.transform.html#pandas.Series.transform" title="pandas.Series.transform">Series.transform</a>(func[, axis])</td>
        <td>Call func on self producing a Series with transformed values and that has the same axis length as self.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.map.html#pandas.Series.map" title="pandas.Series.map">Series.map</a>(arg[, na_action])</td>
        <td>Map values of Series according to input correspondence.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.groupby.html#pandas.Series.groupby" title="pandas.Series.groupby">Series.groupby</a>([by, axis, level, as_index, …])</td>
        <td>Group DataFrame or Series using a mapper or by a Series of columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rolling.html#pandas.Series.rolling" title="pandas.Series.rolling">Series.rolling</a>(window[, min_periods, …])</td>
        <td>Provides rolling window calculations.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.expanding.html#pandas.Series.expanding" title="pandas.Series.expanding">Series.expanding</a>([min_periods, center, axis])</td>
        <td>Provides expanding transformations.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.ewm.html#pandas.Series.ewm" title="pandas.Series.ewm">Series.ewm</a>([com, span, halflife, alpha, …])</td>
        <td>Provides exponential weighted functions.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.pipe.html#pandas.Series.pipe" title="pandas.Series.pipe">Series.pipe</a>(func, *args, **kwargs)</td>
        <td>Apply func(self, *args, **kwargs).</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Computations / Descriptive Stats</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.abs.html#pandas.Series.abs" title="pandas.Series.abs">Series.abs</a>()</td>
        <td>Return a Series/DataFrame with absolute numeric value of each element.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.all.html#pandas.Series.all" title="pandas.Series.all">Series.all</a>([axis, bool_only, skipna, level])</td>
        <td>Return whether all elements are True, potentially over an axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.any.html#pandas.Series.any" title="pandas.Series.any">Series.any</a>([axis, bool_only, skipna, level])</td>
        <td>Return whether any element is True, potentially over an axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.autocorr.html#pandas.Series.autocorr" title="pandas.Series.autocorr">Series.autocorr</a>([lag])</td>
        <td>Compute the lag-N autocorrelation.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.between.html#pandas.Series.between" title="pandas.Series.between">Series.between</a>(left, right[, inclusive])</td>
        <td>Return boolean Series equivalent to left &lt;= series &lt;= right.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.clip.html#pandas.Series.clip" title="pandas.Series.clip">Series.clip</a>([lower, upper, axis, inplace])</td>
        <td>Trim values at input threshold(s).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.clip_lower.html#pandas.Series.clip_lower" title="pandas.Series.clip_lower">Series.clip_lower</a>(threshold[, axis, inplace])</td>
        <td>(DEPRECATED) Trim values below a given threshold.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.clip_upper.html#pandas.Series.clip_upper" title="pandas.Series.clip_upper">Series.clip_upper</a>(threshold[, axis, inplace])</td>
        <td>(DEPRECATED) Trim values above a given threshold.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.corr.html#pandas.Series.corr" title="pandas.Series.corr">Series.corr</a>(other[, method, min_periods])</td>
        <td>Compute correlation with other Series, excluding missing values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.count.html#pandas.Series.count" title="pandas.Series.count">Series.count</a>([level])</td>
        <td>Return number of non-NA/null observations in the Series.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cov.html#pandas.Series.cov" title="pandas.Series.cov">Series.cov</a>(other[, min_periods])</td>
        <td>Compute covariance with Series, excluding missing values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cummax.html#pandas.Series.cummax" title="pandas.Series.cummax">Series.cummax</a>([axis, skipna])</td>
        <td>Return cumulative maximum over a DataFrame or Series axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cummin.html#pandas.Series.cummin" title="pandas.Series.cummin">Series.cummin</a>([axis, skipna])</td>
        <td>Return cumulative minimum over a DataFrame or Series axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cumprod.html#pandas.Series.cumprod" title="pandas.Series.cumprod">Series.cumprod</a>([axis, skipna])</td>
        <td>Return cumulative product over a DataFrame or Series axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cumsum.html#pandas.Series.cumsum" title="pandas.Series.cumsum">Series.cumsum</a>([axis, skipna])</td>
        <td>Return cumulative sum over a DataFrame or Series axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.describe.html#pandas.Series.describe" title="pandas.Series.describe">Series.describe</a>([percentiles, include, exclude])</td>
        <td>Generate descriptive statistics that summarize the central tendency, dispersion and shape of a dataset&rsquo;s distribution, excluding NaN values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.diff.html#pandas.Series.diff" title="pandas.Series.diff">Series.diff</a>([periods])</td>
        <td>First discrete difference of element.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.factorize.html#pandas.Series.factorize" title="pandas.Series.factorize">Series.factorize</a>([sort, na_sentinel])</td>
        <td>Encode the object as an enumerated type or categorical variable.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.kurt.html#pandas.Series.kurt" title="pandas.Series.kurt">Series.kurt</a>([axis, skipna, level, numeric_only])</td>
        <td>Return unbiased kurtosis over requested axis using Fisher&rsquo;s definition of kurtosis (kurtosis of normal == 0.0).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.mad.html#pandas.Series.mad" title="pandas.Series.mad">Series.mad</a>([axis, skipna, level])</td>
        <td>Return the mean absolute deviation of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.max.html#pandas.Series.max" title="pandas.Series.max">Series.max</a>([axis, skipna, level, numeric_only])</td>
        <td>Return the maximum of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.mean.html#pandas.Series.mean" title="pandas.Series.mean">Series.mean</a>([axis, skipna, level, numeric_only])</td>
        <td>Return the mean of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.median.html#pandas.Series.median" title="pandas.Series.median">Series.median</a>([axis, skipna, level, …])</td>
        <td>Return the median of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.min.html#pandas.Series.min" title="pandas.Series.min">Series.min</a>([axis, skipna, level, numeric_only])</td>
        <td>Return the minimum of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.mode.html#pandas.Series.mode" title="pandas.Series.mode">Series.mode</a>([dropna])</td>
        <td>Return the mode(s) of the dataset.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.nlargest.html#pandas.Series.nlargest" title="pandas.Series.nlargest">Series.nlargest</a>([n, keep])</td>
        <td>Return the largest n elements.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.nsmallest.html#pandas.Series.nsmallest" title="pandas.Series.nsmallest">Series.nsmallest</a>([n, keep])</td>
        <td>Return the smallest n elements.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.pct_change.html#pandas.Series.pct_change" title="pandas.Series.pct_change">Series.pct_change</a>([periods, fill_method, …])</td>
        <td>Percentage change between the current and a prior element.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.prod.html#pandas.Series.prod" title="pandas.Series.prod">Series.prod</a>([axis, skipna, level, …])</td>
        <td>Return the product of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.quantile.html#pandas.Series.quantile" title="pandas.Series.quantile">Series.quantile</a>([q, interpolation])</td>
        <td>Return value at the given quantile.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rank.html#pandas.Series.rank" title="pandas.Series.rank">Series.rank</a>([axis, method, numeric_only, …])</td>
        <td>Compute numerical data ranks (1 through n) along axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sem.html#pandas.Series.sem" title="pandas.Series.sem">Series.sem</a>([axis, skipna, level, ddof, …])</td>
        <td>Return unbiased standard error of the mean over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.skew.html#pandas.Series.skew" title="pandas.Series.skew">Series.skew</a>([axis, skipna, level, numeric_only])</td>
        <td>Return unbiased skew over requested axis Normalized by N-1.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.std.html#pandas.Series.std" title="pandas.Series.std">Series.std</a>([axis, skipna, level, ddof, …])</td>
        <td>Return sample standard deviation over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sum.html#pandas.Series.sum" title="pandas.Series.sum">Series.sum</a>([axis, skipna, level, …])</td>
        <td>Return the sum of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.var.html#pandas.Series.var" title="pandas.Series.var">Series.var</a>([axis, skipna, level, ddof, …])</td>
        <td>Return unbiased variance over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.kurtosis.html#pandas.Series.kurtosis" title="pandas.Series.kurtosis">Series.kurtosis</a>([axis, skipna, level, …])</td>
        <td>Return unbiased kurtosis over requested axis using Fisher&rsquo;s definition of kurtosis (kurtosis of normal == 0.0).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.unique.html#pandas.Series.unique" title="pandas.Series.unique">Series.unique</a>()</td>
        <td>Return unique values of Series object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.nunique.html#pandas.Series.nunique" title="pandas.Series.nunique">Series.nunique</a>([dropna])</td>
        <td>Return number of unique elements in the object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.is_unique.html#pandas.Series.is_unique" title="pandas.Series.is_unique">Series.is_unique</a></td>
        <td>Return boolean if values in the object are unique.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.is_monotonic.html#pandas.Series.is_monotonic" title="pandas.Series.is_monotonic">Series.is_monotonic</a></td>
        <td>Return boolean if values in the object are monotonic_increasing.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.is_monotonic_increasing.html#pandas.Series.is_monotonic_increasing" title="pandas.Series.is_monotonic_increasing">Series.is_monotonic_increasing</a></td>
        <td>Return boolean if values in the object are monotonic_increasing.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.is_monotonic_decreasing.html#pandas.Series.is_monotonic_decreasing" title="pandas.Series.is_monotonic_decreasing">Series.is_monotonic_decreasing</a></td>
        <td>Return boolean if values in the object are monotonic_decreasing.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.value_counts.html#pandas.Series.value_counts" title="pandas.Series.value_counts">Series.value_counts</a>([normalize, sort, …])</td>
        <td>Return a Series containing counts of unique values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.compound.html#pandas.Series.compound" title="pandas.Series.compound">Series.compound</a>([axis, skipna, level])</td>
        <td>Return the compound percentage of the values for the requested axis.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Reindexing / Selection / Label manipulation</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.align.html#pandas.Series.align" title="pandas.Series.align">Series.align</a>(other[, join, axis, level, …])</td>
        <td>Align two objects on their axes with the specified join method for each axis Index.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.drop.html#pandas.Series.drop" title="pandas.Series.drop">Series.drop</a>([labels, axis, index, columns, …])</td>
        <td>Return Series with specified index labels removed.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.droplevel.html#pandas.Series.droplevel" title="pandas.Series.droplevel">Series.droplevel</a>(level[, axis])</td>
        <td>Return DataFrame with requested index / column level(s) removed.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.drop_duplicates.html#pandas.Series.drop_duplicates" title="pandas.Series.drop_duplicates">Series.drop_duplicates</a>([keep, inplace])</td>
        <td>Return Series with duplicate values removed.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.duplicated.html#pandas.Series.duplicated" title="pandas.Series.duplicated">Series.duplicated</a>([keep])</td>
        <td>Indicate duplicate Series values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.equals.html#pandas.Series.equals" title="pandas.Series.equals">Series.equals</a>(other)</td>
        <td>Test whether two objects contain the same elements.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.first.html#pandas.Series.first" title="pandas.Series.first">Series.first</a>(offset)</td>
        <td>Convenience method for subsetting initial periods of time series data based on a date offset.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.head.html#pandas.Series.head" title="pandas.Series.head">Series.head</a>([n])</td>
        <td>Return the first n rows.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.idxmax.html#pandas.Series.idxmax" title="pandas.Series.idxmax">Series.idxmax</a>([axis, skipna])</td>
        <td>Return the row label of the maximum value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.idxmin.html#pandas.Series.idxmin" title="pandas.Series.idxmin">Series.idxmin</a>([axis, skipna])</td>
        <td>Return the row label of the minimum value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.isin.html#pandas.Series.isin" title="pandas.Series.isin">Series.isin</a>(values)</td>
        <td>Check whether values are contained in Series.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.last.html#pandas.Series.last" title="pandas.Series.last">Series.last</a>(offset)</td>
        <td>Convenience method for subsetting final periods of time series data based on a date offset.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.reindex.html#pandas.Series.reindex" title="pandas.Series.reindex">Series.reindex</a>([index])</td>
        <td>Conform Series to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.reindex_like.html#pandas.Series.reindex_like" title="pandas.Series.reindex_like">Series.reindex_like</a>(other[, method, copy, …])</td>
        <td>Return an object with matching indices as other object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rename.html#pandas.Series.rename" title="pandas.Series.rename">Series.rename</a>([index])</td>
        <td>Alter Series index labels or name.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.rename_axis.html#pandas.Series.rename_axis" title="pandas.Series.rename_axis">Series.rename_axis</a>([mapper, index, columns, …])</td>
        <td>Set the name of the axis for the index or columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.reset_index.html#pandas.Series.reset_index" title="pandas.Series.reset_index">Series.reset_index</a>([level, drop, name, inplace])</td>
        <td>Generate a new DataFrame or Series with the index reset.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sample.html#pandas.Series.sample" title="pandas.Series.sample">Series.sample</a>([n, frac, replace, weights, …])</td>
        <td>Return a random sample of items from an axis of object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.select.html#pandas.Series.select" title="pandas.Series.select">Series.select</a>(crit[, axis])</td>
        <td>(DEPRECATED) Return data corresponding to axis labels matching criteria.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.set_axis.html#pandas.Series.set_axis" title="pandas.Series.set_axis">Series.set_axis</a>(labels[, axis, inplace])</td>
        <td>Assign desired index to given axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.take.html#pandas.Series.take" title="pandas.Series.take">Series.take</a>(indices[, axis, convert, is_copy])</td>
        <td>Return the elements in the given <em>positional</em> indices along an axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.tail.html#pandas.Series.tail" title="pandas.Series.tail">Series.tail</a>([n])</td>
        <td>Return the last n rows.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.truncate.html#pandas.Series.truncate" title="pandas.Series.truncate">Series.truncate</a>([before, after, axis, copy])</td>
        <td>Truncate a Series or DataFrame before and after some index value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.where.html#pandas.Series.where" title="pandas.Series.where">Series.where</a>(cond[, other, inplace, axis, …])</td>
        <td>Replace values where the condition is False.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.mask.html#pandas.Series.mask" title="pandas.Series.mask">Series.mask</a>(cond[, other, inplace, axis, …])</td>
        <td>Replace values where the condition is True.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.add_prefix.html#pandas.Series.add_prefix" title="pandas.Series.add_prefix">Series.add_prefix</a>(prefix)</td>
        <td>Prefix labels with string prefix.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.add_suffix.html#pandas.Series.add_suffix" title="pandas.Series.add_suffix">Series.add_suffix</a>(suffix)</td>
        <td>Suffix labels with string suffix.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.filter.html#pandas.Series.filter" title="pandas.Series.filter">Series.filter</a>([items, like, regex, axis])</td>
        <td>Subset rows or columns of dataframe according to labels in the specified index.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Missing data handling</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.isna.html#pandas.Series.isna" title="pandas.Series.isna">Series.isna</a>()</td>
        <td>Detect missing values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.notna.html#pandas.Series.notna" title="pandas.Series.notna">Series.notna</a>()</td>
        <td>Detect existing (non-missing) values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dropna.html#pandas.Series.dropna" title="pandas.Series.dropna">Series.dropna</a>([axis, inplace])</td>
        <td>Return a new Series with missing values removed.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.fillna.html#pandas.Series.fillna" title="pandas.Series.fillna">Series.fillna</a>([value, method, axis, …])</td>
        <td>Fill NA/NaN values using the specified method.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.interpolate.html#pandas.Series.interpolate" title="pandas.Series.interpolate">Series.interpolate</a>([method, axis, limit, …])</td>
        <td>Interpolate values according to different methods.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Reshaping, sorting</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.argsort.html#pandas.Series.argsort" title="pandas.Series.argsort">Series.argsort</a>([axis, kind, order])</td>
        <td>Overrides ndarray.argsort.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.argmin.html#pandas.Series.argmin" title="pandas.Series.argmin">Series.argmin</a>([axis, skipna])</td>
        <td>(DEPRECATED) Return the row label of the minimum value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.argmax.html#pandas.Series.argmax" title="pandas.Series.argmax">Series.argmax</a>([axis, skipna])</td>
        <td>(DEPRECATED) Return the row label of the maximum value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.reorder_levels.html#pandas.Series.reorder_levels" title="pandas.Series.reorder_levels">Series.reorder_levels</a>(order)</td>
        <td>Rearrange index levels using input order.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sort_values.html#pandas.Series.sort_values" title="pandas.Series.sort_values">Series.sort_values</a>([axis, ascending, …])</td>
        <td>Sort by the values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sort_index.html#pandas.Series.sort_index" title="pandas.Series.sort_index">Series.sort_index</a>([axis, level, ascending, …])</td>
        <td>Sort Series by index labels.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.swaplevel.html#pandas.Series.swaplevel" title="pandas.Series.swaplevel">Series.swaplevel</a>([i, j, copy])</td>
        <td>Swap levels i and j in a MultiIndex.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.unstack.html#pandas.Series.unstack" title="pandas.Series.unstack">Series.unstack</a>([level, fill_value])</td>
        <td>Unstack, a.k.a.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.searchsorted.html#pandas.Series.searchsorted" title="pandas.Series.searchsorted">Series.searchsorted</a>(value[, side, sorter])</td>
        <td>Find indices where elements should be inserted to maintain order.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.ravel.html#pandas.Series.ravel" title="pandas.Series.ravel">Series.ravel</a>([order])</td>
        <td>Return the flattened underlying data as an ndarray.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.repeat.html#pandas.Series.repeat" title="pandas.Series.repeat">Series.repeat</a>(repeats[, axis])</td>
        <td>Repeat elements of a Series.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.squeeze.html#pandas.Series.squeeze" title="pandas.Series.squeeze">Series.squeeze</a>([axis])</td>
        <td>Squeeze 1 dimensional axis objects into scalars.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.view.html#pandas.Series.view" title="pandas.Series.view">Series.view</a>([dtype])</td>
        <td>Create a new view of the Series.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Combining / joining / merging</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.append.html#pandas.Series.append" title="pandas.Series.append">Series.append</a>(to_append[, ignore_index, …])</td>
        <td>Concatenate two or more Series.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.replace.html#pandas.Series.replace" title="pandas.Series.replace">Series.replace</a>([to_replace, value, inplace, …])</td>
        <td>Replace values given in to_replace with value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.update.html#pandas.Series.update" title="pandas.Series.update">Series.update</a>(other)</td>
        <td>Modify Series in place using non-NA values from passed Series.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Time series-related</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.asfreq.html#pandas.Series.asfreq" title="pandas.Series.asfreq">Series.asfreq</a>(freq[, method, how, …])</td>
        <td>Convert TimeSeries to specified frequency.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.asof.html#pandas.Series.asof" title="pandas.Series.asof">Series.asof</a>(where[, subset])</td>
        <td>Return the last row(s) without any NaNs before where.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.shift.html#pandas.Series.shift" title="pandas.Series.shift">Series.shift</a>([periods, freq, axis, fill_value])</td>
        <td>Shift index by desired number of periods with an optional time freq.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.first_valid_index.html#pandas.Series.first_valid_index" title="pandas.Series.first_valid_index">Series.first_valid_index</a>()</td>
        <td>Return index for first non-NA/null value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.last_valid_index.html#pandas.Series.last_valid_index" title="pandas.Series.last_valid_index">Series.last_valid_index</a>()</td>
        <td>Return index for last non-NA/null value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.resample.html#pandas.Series.resample" title="pandas.Series.resample">Series.resample</a>(rule[, how, axis, …])</td>
        <td>Resample time-series data.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.tz_convert.html#pandas.Series.tz_convert" title="pandas.Series.tz_convert">Series.tz_convert</a>(tz[, axis, level, copy])</td>
        <td>Convert tz-aware axis to target time zone.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.tz_localize.html#pandas.Series.tz_localize" title="pandas.Series.tz_localize">Series.tz_localize</a>(tz[, axis, level, copy, …])</td>
        <td>Localize tz-naive index of a Series or DataFrame to target time zone.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.at_time.html#pandas.Series.at_time" title="pandas.Series.at_time">Series.at_time</a>(time[, asof, axis])</td>
        <td>Select values at particular time of day (e.g.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.between_time.html#pandas.Series.between_time" title="pandas.Series.between_time">Series.between_time</a>(start_time, end_time[, …])</td>
        <td>Select values between particular times of the day (e.g., 9:00-9:30 AM).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.tshift.html#pandas.Series.tshift" title="pandas.Series.tshift">Series.tshift</a>([periods, freq, axis])</td>
        <td>Shift the time index, using the index&rsquo;s frequency if available.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.slice_shift.html#pandas.Series.slice_shift" title="pandas.Series.slice_shift">Series.slice_shift</a>([periods, axis])</td>
        <td>Equivalent to shift without copying data.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Accessors</h2>
  <p>Pandas provides dtype-specific methods under various accessors. These are separate namespaces within <a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.html#pandas.Series" title="pandas.Series">Series</a>that only apply to specific data types.</p>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="45%">
    <col width="55%">
    </colgroup>
    <thead valign="bottom">
      <tr>
        <th>Data Type</th>
        <th>Accessor</th>
      </tr>
    </thead>
    <tbody valign="top">
      <tr>
        <td>Datetime, Timedelta, Period</td>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/series.html#api-series-dt">dt</a></td>
      </tr>
      <tr>
        <td>String</td>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/series.html#api-series-str">str</a></td>
      </tr>
      <tr>
        <td>Categorical</td>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/series.html#api-series-cat">cat</a></td>
      </tr>
      <tr>
        <td>Sparse</td>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/series.html#api-series-sparse">sparse</a></td>
      </tr>
    </tbody>
  </table>
  <div class="w3-container">
    <h3>Datetimelike Properties</h3>
    <p>Series.dt can be used to access the values of the series as datetimelike and return several properties. These can be accessed like Series.dt.&lt;property&gt;.</p>
    <div class="w3-container">
      <h4>Datetime Properties</h4>
      <table class="w3-table-all w3-hoverable">
        <colgroup>
        <col width="10%">
        <col width="90%">
        </colgroup>
        <tbody valign="top">
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.date.html#pandas.Series.dt.date" title="pandas.Series.dt.date">Series.dt.date</a></td>
            <td>Returns numpy array of python datetime.date objects (namely, the date part of Timestamps without timezone information).</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.time.html#pandas.Series.dt.time" title="pandas.Series.dt.time">Series.dt.time</a></td>
            <td>Returns numpy array of datetime.time.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.timetz.html#pandas.Series.dt.timetz" title="pandas.Series.dt.timetz">Series.dt.timetz</a></td>
            <td>Returns numpy array of datetime.time also containing timezone information.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.year.html#pandas.Series.dt.year" title="pandas.Series.dt.year">Series.dt.year</a></td>
            <td>The year of the datetime.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.month.html#pandas.Series.dt.month" title="pandas.Series.dt.month">Series.dt.month</a></td>
            <td>The month as January=1, December=12.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.day.html#pandas.Series.dt.day" title="pandas.Series.dt.day">Series.dt.day</a></td>
            <td>The days of the datetime.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.hour.html#pandas.Series.dt.hour" title="pandas.Series.dt.hour">Series.dt.hour</a></td>
            <td>The hours of the datetime.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.minute.html#pandas.Series.dt.minute" title="pandas.Series.dt.minute">Series.dt.minute</a></td>
            <td>The minutes of the datetime.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.second.html#pandas.Series.dt.second" title="pandas.Series.dt.second">Series.dt.second</a></td>
            <td>The seconds of the datetime.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.microsecond.html#pandas.Series.dt.microsecond" title="pandas.Series.dt.microsecond">Series.dt.microsecond</a></td>
            <td>The microseconds of the datetime.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.nanosecond.html#pandas.Series.dt.nanosecond" title="pandas.Series.dt.nanosecond">Series.dt.nanosecond</a></td>
            <td>The nanoseconds of the datetime.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.week.html#pandas.Series.dt.week" title="pandas.Series.dt.week">Series.dt.week</a></td>
            <td>The week ordinal of the year.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.weekofyear.html#pandas.Series.dt.weekofyear" title="pandas.Series.dt.weekofyear">Series.dt.weekofyear</a></td>
            <td>The week ordinal of the year.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.dayofweek.html#pandas.Series.dt.dayofweek" title="pandas.Series.dt.dayofweek">Series.dt.dayofweek</a></td>
            <td>The day of the week with Monday=0, Sunday=6.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.weekday.html#pandas.Series.dt.weekday" title="pandas.Series.dt.weekday">Series.dt.weekday</a></td>
            <td>The day of the week with Monday=0, Sunday=6.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.dayofyear.html#pandas.Series.dt.dayofyear" title="pandas.Series.dt.dayofyear">Series.dt.dayofyear</a></td>
            <td>The ordinal day of the year.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.quarter.html#pandas.Series.dt.quarter" title="pandas.Series.dt.quarter">Series.dt.quarter</a></td>
            <td>The quarter of the date.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.is_month_start.html#pandas.Series.dt.is_month_start" title="pandas.Series.dt.is_month_start">Series.dt.is_month_start</a></td>
            <td>Indicates whether the date is the first day of the month.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.is_month_end.html#pandas.Series.dt.is_month_end" title="pandas.Series.dt.is_month_end">Series.dt.is_month_end</a></td>
            <td>Indicates whether the date is the last day of the month.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.is_quarter_start.html#pandas.Series.dt.is_quarter_start" title="pandas.Series.dt.is_quarter_start">Series.dt.is_quarter_start</a></td>
            <td>Indicator for whether the date is the first day of a quarter.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.is_quarter_end.html#pandas.Series.dt.is_quarter_end" title="pandas.Series.dt.is_quarter_end">Series.dt.is_quarter_end</a></td>
            <td>Indicator for whether the date is the last day of a quarter.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.is_year_start.html#pandas.Series.dt.is_year_start" title="pandas.Series.dt.is_year_start">Series.dt.is_year_start</a></td>
            <td>Indicate whether the date is the first day of a year.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.is_year_end.html#pandas.Series.dt.is_year_end" title="pandas.Series.dt.is_year_end">Series.dt.is_year_end</a></td>
            <td>Indicate whether the date is the last day of the year.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.is_leap_year.html#pandas.Series.dt.is_leap_year" title="pandas.Series.dt.is_leap_year">Series.dt.is_leap_year</a></td>
            <td>Boolean indicator if the date belongs to a leap year.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.daysinmonth.html#pandas.Series.dt.daysinmonth" title="pandas.Series.dt.daysinmonth">Series.dt.daysinmonth</a></td>
            <td>The number of days in the month.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.days_in_month.html#pandas.Series.dt.days_in_month" title="pandas.Series.dt.days_in_month">Series.dt.days_in_month</a></td>
            <td>The number of days in the month.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.tz.html#pandas.Series.dt.tz" title="pandas.Series.dt.tz">Series.dt.tz</a></td>
            <td>Return timezone, if any.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.freq.html#pandas.Series.dt.freq" title="pandas.Series.dt.freq">Series.dt.freq</a></td>
            <td></td>
          </tr>
        </tbody>
      </table>
    </div>
    <div class="w3-container">
      <h4>Datetime Methods</h4>
      <table class="w3-table-all w3-hoverable">
        <colgroup>
        <col width="10%">
        <col width="90%">
        </colgroup>
        <tbody valign="top">
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.to_period.html#pandas.Series.dt.to_period" title="pandas.Series.dt.to_period">Series.dt.to_period</a>(*args, **kwargs)</td>
            <td>Cast to PeriodArray/Index at a particular frequency.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.to_pydatetime.html#pandas.Series.dt.to_pydatetime" title="pandas.Series.dt.to_pydatetime">Series.dt.to_pydatetime</a>()</td>
            <td>Return the data as an array of native Python datetime objects.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.tz_localize.html#pandas.Series.dt.tz_localize" title="pandas.Series.dt.tz_localize">Series.dt.tz_localize</a>(*args, **kwargs)</td>
            <td>Localize tz-naive Datetime Array/Index to tz-aware Datetime Array/Index.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.tz_convert.html#pandas.Series.dt.tz_convert" title="pandas.Series.dt.tz_convert">Series.dt.tz_convert</a>(*args, **kwargs)</td>
            <td>Convert tz-aware Datetime Array/Index from one time zone to another.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.normalize.html#pandas.Series.dt.normalize" title="pandas.Series.dt.normalize">Series.dt.normalize</a>(*args, **kwargs)</td>
            <td>Convert times to midnight.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.strftime.html#pandas.Series.dt.strftime" title="pandas.Series.dt.strftime">Series.dt.strftime</a>(*args, **kwargs)</td>
            <td>Convert to Index using specified date_format.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.round.html#pandas.Series.dt.round" title="pandas.Series.dt.round">Series.dt.round</a>(*args, **kwargs)</td>
            <td>Perform round operation on the data to the specified freq.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.floor.html#pandas.Series.dt.floor" title="pandas.Series.dt.floor">Series.dt.floor</a>(*args, **kwargs)</td>
            <td>Perform floor operation on the data to the specified freq.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.ceil.html#pandas.Series.dt.ceil" title="pandas.Series.dt.ceil">Series.dt.ceil</a>(*args, **kwargs)</td>
            <td>Perform ceil operation on the data to the specified freq.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.month_name.html#pandas.Series.dt.month_name" title="pandas.Series.dt.month_name">Series.dt.month_name</a>(*args, **kwargs)</td>
            <td>Return the month names of the DateTimeIndex with specified locale.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.day_name.html#pandas.Series.dt.day_name" title="pandas.Series.dt.day_name">Series.dt.day_name</a>(*args, **kwargs)</td>
            <td>Return the day names of the DateTimeIndex with specified locale.</td>
          </tr>
        </tbody>
      </table>
    </div>
    <div class="w3-container">
      <h4>Period Properties</h4>
      <table class="w3-table-all w3-hoverable">
        <colgroup>
        <col width="10%">
        <col width="90%">
        </colgroup>
        <tbody valign="top">
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.qyear.html#pandas.Series.dt.qyear" title="pandas.Series.dt.qyear">Series.dt.qyear</a></td>
            <td></td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.start_time.html#pandas.Series.dt.start_time" title="pandas.Series.dt.start_time">Series.dt.start_time</a></td>
            <td></td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.end_time.html#pandas.Series.dt.end_time" title="pandas.Series.dt.end_time">Series.dt.end_time</a></td>
            <td></td>
          </tr>
        </tbody>
      </table>
    </div>
    <div class="w3-container">
      <h4>Timedelta Properties</h4>
      <table class="w3-table-all w3-hoverable">
        <colgroup>
        <col width="10%">
        <col width="90%">
        </colgroup>
        <tbody valign="top">
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.days.html#pandas.Series.dt.days" title="pandas.Series.dt.days">Series.dt.days</a></td>
            <td>Number of days for each element.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.seconds.html#pandas.Series.dt.seconds" title="pandas.Series.dt.seconds">Series.dt.seconds</a></td>
            <td>Number of seconds (&gt;= 0 and less than 1 day) for each element.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.microseconds.html#pandas.Series.dt.microseconds" title="pandas.Series.dt.microseconds">Series.dt.microseconds</a></td>
            <td>Number of microseconds (&gt;= 0 and less than 1 second) for each element.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.nanoseconds.html#pandas.Series.dt.nanoseconds" title="pandas.Series.dt.nanoseconds">Series.dt.nanoseconds</a></td>
            <td>Number of nanoseconds (&gt;= 0 and less than 1 microsecond) for each element.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.components.html#pandas.Series.dt.components" title="pandas.Series.dt.components">Series.dt.components</a></td>
            <td>Return a Dataframe of the components of the Timedeltas.</td>
          </tr>
        </tbody>
      </table>
    </div>
    <div class="w3-container">
      <h4>Timedelta Methods</h4>
      <table class="w3-table-all w3-hoverable">
        <colgroup>
        <col width="10%">
        <col width="90%">
        </colgroup>
        <tbody valign="top">
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.to_pytimedelta.html#pandas.Series.dt.to_pytimedelta" title="pandas.Series.dt.to_pytimedelta">Series.dt.to_pytimedelta</a>()</td>
            <td>Return an array of native datetime.timedelta objects.</td>
          </tr>
          <tr>
            <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.total_seconds.html#pandas.Series.dt.total_seconds" title="pandas.Series.dt.total_seconds">Series.dt.total_seconds</a>(*args, **kwargs)</td>
            <td>Return total duration of each element expressed in seconds.</td>
          </tr>
        </tbody>
      </table>
    </div>
  </div>
  <div class="w3-container">
    <h3>String handling</h3>
    <p>Series.str can be used to access the values of the series as strings and apply several methods to it. These can be accessed like Series.str.&lt;function/property&gt;.</p>
    <table class="w3-table-all w3-hoverable">
      <colgroup>
      <col width="10%">
      <col width="90%">
      </colgroup>
      <tbody valign="top">
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.capitalize.html#pandas.Series.str.capitalize" title="pandas.Series.str.capitalize">Series.str.capitalize</a>()</td>
          <td>Convert strings in the Series/Index to be capitalized.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.cat.html#pandas.Series.str.cat" title="pandas.Series.str.cat">Series.str.cat</a>([others, sep, na_rep, join])</td>
          <td>Concatenate strings in the Series/Index with given separator.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.center.html#pandas.Series.str.center" title="pandas.Series.str.center">Series.str.center</a>(width[, fillchar])</td>
          <td>Filling left and right side of strings in the Series/Index with an additional character.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.contains.html#pandas.Series.str.contains" title="pandas.Series.str.contains">Series.str.contains</a>(pat[, case, flags, na, …])</td>
          <td>Test if pattern or regex is contained within a string of a Series or Index.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.count.html#pandas.Series.str.count" title="pandas.Series.str.count">Series.str.count</a>(pat[, flags])</td>
          <td>Count occurrences of pattern in each string of the Series/Index.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.decode.html#pandas.Series.str.decode" title="pandas.Series.str.decode">Series.str.decode</a>(encoding[, errors])</td>
          <td>Decode character string in the Series/Index using indicated encoding.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.encode.html#pandas.Series.str.encode" title="pandas.Series.str.encode">Series.str.encode</a>(encoding[, errors])</td>
          <td>Encode character string in the Series/Index using indicated encoding.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.endswith.html#pandas.Series.str.endswith" title="pandas.Series.str.endswith">Series.str.endswith</a>(pat[, na])</td>
          <td>Test if the end of each string element matches a pattern.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.extract.html#pandas.Series.str.extract" title="pandas.Series.str.extract">Series.str.extract</a>(pat[, flags, expand])</td>
          <td>Extract capture groups in the regex pat as columns in a DataFrame.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.extractall.html#pandas.Series.str.extractall" title="pandas.Series.str.extractall">Series.str.extractall</a>(pat[, flags])</td>
          <td>For each subject string in the Series, extract groups from all matches of regular expression pat.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.find.html#pandas.Series.str.find" title="pandas.Series.str.find">Series.str.find</a>(sub[, start, end])</td>
          <td>Return lowest indexes in each strings in the Series/Index where the substring is fully contained between [start:end].</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.findall.html#pandas.Series.str.findall" title="pandas.Series.str.findall">Series.str.findall</a>(pat[, flags])</td>
          <td>Find all occurrences of pattern or regular expression in the Series/Index.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.get.html#pandas.Series.str.get" title="pandas.Series.str.get">Series.str.get</a>(i)</td>
          <td>Extract element from each component at specified position.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.index.html#pandas.Series.str.index" title="pandas.Series.str.index">Series.str.index</a>(sub[, start, end])</td>
          <td>Return lowest indexes in each strings where the substring is fully contained between [start:end].</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.join.html#pandas.Series.str.join" title="pandas.Series.str.join">Series.str.join</a>(sep)</td>
          <td>Join lists contained as elements in the Series/Index with passed delimiter.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.len.html#pandas.Series.str.len" title="pandas.Series.str.len">Series.str.len</a>()</td>
          <td>Computes the length of each element in the Series/Index.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.ljust.html#pandas.Series.str.ljust" title="pandas.Series.str.ljust">Series.str.ljust</a>(width[, fillchar])</td>
          <td>Filling right side of strings in the Series/Index with an additional character.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.lower.html#pandas.Series.str.lower" title="pandas.Series.str.lower">Series.str.lower</a>()</td>
          <td>Convert strings in the Series/Index to lowercase.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.lstrip.html#pandas.Series.str.lstrip" title="pandas.Series.str.lstrip">Series.str.lstrip</a>([to_strip])</td>
          <td>Remove leading and trailing characters.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.match.html#pandas.Series.str.match" title="pandas.Series.str.match">Series.str.match</a>(pat[, case, flags, na])</td>
          <td>Determine if each string matches a regular expression.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.normalize.html#pandas.Series.str.normalize" title="pandas.Series.str.normalize">Series.str.normalize</a>(form)</td>
          <td>Return the Unicode normal form for the strings in the Series/Index.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.pad.html#pandas.Series.str.pad" title="pandas.Series.str.pad">Series.str.pad</a>(width[, side, fillchar])</td>
          <td>Pad strings in the Series/Index up to width.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.partition.html#pandas.Series.str.partition" title="pandas.Series.str.partition">Series.str.partition</a>([sep, expand])</td>
          <td>Split the string at the first occurrence of sep.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.repeat.html#pandas.Series.str.repeat" title="pandas.Series.str.repeat">Series.str.repeat</a>(repeats)</td>
          <td>Duplicate each string in the Series or Index.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.replace.html#pandas.Series.str.replace" title="pandas.Series.str.replace">Series.str.replace</a>(pat, repl[, n, case, …])</td>
          <td>Replace occurrences of pattern/regex in the Series/Index with some other string.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.rfind.html#pandas.Series.str.rfind" title="pandas.Series.str.rfind">Series.str.rfind</a>(sub[, start, end])</td>
          <td>Return highest indexes in each strings in the Series/Index where the substring is fully contained between [start:end].</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.rindex.html#pandas.Series.str.rindex" title="pandas.Series.str.rindex">Series.str.rindex</a>(sub[, start, end])</td>
          <td>Return highest indexes in each strings where the substring is fully contained between [start:end].</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.rjust.html#pandas.Series.str.rjust" title="pandas.Series.str.rjust">Series.str.rjust</a>(width[, fillchar])</td>
          <td>Filling left side of strings in the Series/Index with an additional character.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.rpartition.html#pandas.Series.str.rpartition" title="pandas.Series.str.rpartition">Series.str.rpartition</a>([sep, expand])</td>
          <td>Split the string at the last occurrence of sep.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.rstrip.html#pandas.Series.str.rstrip" title="pandas.Series.str.rstrip">Series.str.rstrip</a>([to_strip])</td>
          <td>Remove leading and trailing characters.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.slice.html#pandas.Series.str.slice" title="pandas.Series.str.slice">Series.str.slice</a>([start, stop, step])</td>
          <td>Slice substrings from each element in the Series or Index.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.slice_replace.html#pandas.Series.str.slice_replace" title="pandas.Series.str.slice_replace">Series.str.slice_replace</a>([start, stop, repl])</td>
          <td>Replace a positional slice of a string with another value.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.split.html#pandas.Series.str.split" title="pandas.Series.str.split">Series.str.split</a>([pat, n, expand])</td>
          <td>Split strings around given separator/delimiter.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.rsplit.html#pandas.Series.str.rsplit" title="pandas.Series.str.rsplit">Series.str.rsplit</a>([pat, n, expand])</td>
          <td>Split strings around given separator/delimiter.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.startswith.html#pandas.Series.str.startswith" title="pandas.Series.str.startswith">Series.str.startswith</a>(pat[, na])</td>
          <td>Test if the start of each string element matches a pattern.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.strip.html#pandas.Series.str.strip" title="pandas.Series.str.strip">Series.str.strip</a>([to_strip])</td>
          <td>Remove leading and trailing characters.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.swapcase.html#pandas.Series.str.swapcase" title="pandas.Series.str.swapcase">Series.str.swapcase</a>()</td>
          <td>Convert strings in the Series/Index to be swapcased.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.title.html#pandas.Series.str.title" title="pandas.Series.str.title">Series.str.title</a>()</td>
          <td>Convert strings in the Series/Index to titlecase.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.translate.html#pandas.Series.str.translate" title="pandas.Series.str.translate">Series.str.translate</a>(table[, deletechars])</td>
          <td>Map all characters in the string through the given mapping table.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.upper.html#pandas.Series.str.upper" title="pandas.Series.str.upper">Series.str.upper</a>()</td>
          <td>Convert strings in the Series/Index to uppercase.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.wrap.html#pandas.Series.str.wrap" title="pandas.Series.str.wrap">Series.str.wrap</a>(width, **kwargs)</td>
          <td>Wrap long strings in the Series/Index to be formatted in paragraphs with length less than a given width.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.zfill.html#pandas.Series.str.zfill" title="pandas.Series.str.zfill">Series.str.zfill</a>(width)</td>
          <td>Pad strings in the Series/Index by prepending &lsquo;0&rsquo; characters.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.isalnum.html#pandas.Series.str.isalnum" title="pandas.Series.str.isalnum">Series.str.isalnum</a>()</td>
          <td>Check whether all characters in each string are alphanumeric.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.isalpha.html#pandas.Series.str.isalpha" title="pandas.Series.str.isalpha">Series.str.isalpha</a>()</td>
          <td>Check whether all characters in each string are alphabetic.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.isdigit.html#pandas.Series.str.isdigit" title="pandas.Series.str.isdigit">Series.str.isdigit</a>()</td>
          <td>Check whether all characters in each string are digits.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.isspace.html#pandas.Series.str.isspace" title="pandas.Series.str.isspace">Series.str.isspace</a>()</td>
          <td>Check whether all characters in each string are whitespace.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.islower.html#pandas.Series.str.islower" title="pandas.Series.str.islower">Series.str.islower</a>()</td>
          <td>Check whether all characters in each string are lowercase.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.isupper.html#pandas.Series.str.isupper" title="pandas.Series.str.isupper">Series.str.isupper</a>()</td>
          <td>Check whether all characters in each string are uppercase.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.istitle.html#pandas.Series.str.istitle" title="pandas.Series.str.istitle">Series.str.istitle</a>()</td>
          <td>Check whether all characters in each string are titlecase.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.isnumeric.html#pandas.Series.str.isnumeric" title="pandas.Series.str.isnumeric">Series.str.isnumeric</a>()</td>
          <td>Check whether all characters in each string are numeric.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.isdecimal.html#pandas.Series.str.isdecimal" title="pandas.Series.str.isdecimal">Series.str.isdecimal</a>()</td>
          <td>Check whether all characters in each string are decimal.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.get_dummies.html#pandas.Series.str.get_dummies" title="pandas.Series.str.get_dummies">Series.str.get_dummies</a>([sep])</td>
          <td>Split each string in the Series by sep and return a frame of dummy/indicator variables.</td>
        </tr>
      </tbody>
    </table>
  </div>
  <div class="w3-container">
    <h3>Categorical Accessor</h3>
    <p>Categorical-dtype specific methods and attributes are available under the Series.cat accessor.</p>
    <table class="w3-table-all w3-hoverable">
      <colgroup>
      <col width="10%">
      <col width="90%">
      </colgroup>
      <tbody valign="top">
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.categories.html#pandas.Series.cat.categories" title="pandas.Series.cat.categories">Series.cat.categories</a></td>
          <td>The categories of this categorical.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.ordered.html#pandas.Series.cat.ordered" title="pandas.Series.cat.ordered">Series.cat.ordered</a></td>
          <td>Whether the categories have an ordered relationship.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.codes.html#pandas.Series.cat.codes" title="pandas.Series.cat.codes">Series.cat.codes</a></td>
          <td>Return Series of codes as well as the index.</td>
        </tr>
      </tbody>
    </table>
    <table class="w3-table-all w3-hoverable">
      <colgroup>
      <col width="10%">
      <col width="90%">
      </colgroup>
      <tbody valign="top">
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.rename_categories.html#pandas.Series.cat.rename_categories" title="pandas.Series.cat.rename_categories">Series.cat.rename_categories</a>(*args, **kwargs)</td>
          <td>Renames categories.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.reorder_categories.html#pandas.Series.cat.reorder_categories" title="pandas.Series.cat.reorder_categories">Series.cat.reorder_categories</a>(*args, **kwargs)</td>
          <td>Reorders categories as specified in new_categories.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.add_categories.html#pandas.Series.cat.add_categories" title="pandas.Series.cat.add_categories">Series.cat.add_categories</a>(*args, **kwargs)</td>
          <td>Add new categories.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.remove_categories.html#pandas.Series.cat.remove_categories" title="pandas.Series.cat.remove_categories">Series.cat.remove_categories</a>(*args, **kwargs)</td>
          <td>Removes the specified categories.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.remove_unused_categories.html#pandas.Series.cat.remove_unused_categories" title="pandas.Series.cat.remove_unused_categories">Series.cat.remove_unused_categories</a>(*args, …)</td>
          <td>Removes categories which are not used.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.set_categories.html#pandas.Series.cat.set_categories" title="pandas.Series.cat.set_categories">Series.cat.set_categories</a>(*args, **kwargs)</td>
          <td>Sets the categories to the specified new_categories.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.as_ordered.html#pandas.Series.cat.as_ordered" title="pandas.Series.cat.as_ordered">Series.cat.as_ordered</a>(*args, **kwargs)</td>
          <td>Set the Categorical to be ordered.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.as_unordered.html#pandas.Series.cat.as_unordered" title="pandas.Series.cat.as_unordered">Series.cat.as_unordered</a>(*args, **kwargs)</td>
          <td>Set the Categorical to be unordered.</td>
        </tr>
      </tbody>
    </table>
  </div>
</div>
<div class="w3-container">
  <div class="w3-container">
    <h3>Sparse Accessor</h3>
    <p>Sparse-dtype specific methods and attributes are provided under the Series.sparse accessor.</p>
    <table class="w3-table-all w3-hoverable">
      <colgroup>
      <col width="10%">
      <col width="90%">
      </colgroup>
      <tbody valign="top">
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sparse.npoints.html#pandas.Series.sparse.npoints" title="pandas.Series.sparse.npoints">Series.sparse.npoints</a></td>
          <td>The number of non- fill_value points.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sparse.density.html#pandas.Series.sparse.density" title="pandas.Series.sparse.density">Series.sparse.density</a></td>
          <td>The percent of non- fill_value points, as decimal.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sparse.fill_value.html#pandas.Series.sparse.fill_value" title="pandas.Series.sparse.fill_value">Series.sparse.fill_value</a></td>
          <td>Elements in data that are fill_value are not stored.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sparse.sp_values.html#pandas.Series.sparse.sp_values" title="pandas.Series.sparse.sp_values">Series.sparse.sp_values</a></td>
          <td>An ndarray containing the non- fill_value values.</td>
        </tr>
      </tbody>
    </table>
    <table class="w3-table-all w3-hoverable">
      <colgroup>
      <col width="10%">
      <col width="90%">
      </colgroup>
      <tbody valign="top">
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sparse.from_coo.html#pandas.Series.sparse.from_coo" title="pandas.Series.sparse.from_coo">Series.sparse.from_coo</a>(A[, dense_index])</td>
          <td>Create a SparseSeries from a scipy.sparse.coo_matrix.</td>
        </tr>
        <tr>
          <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.sparse.to_coo.html#pandas.Series.sparse.to_coo" title="pandas.Series.sparse.to_coo">Series.sparse.to_coo</a>([row_levels, …])</td>
          <td>Create a scipy.sparse.coo_matrix from a SparseSeries with MultiIndex.</td>
        </tr>
      </tbody>
    </table>
  </div>
</div>
<div class="w3-container">
  <h2>Plotting</h2>
  <p>Series.plot is both a callable method and a namespace attribute for specific plotting methods of the form Series.plot.&lt;kind&gt;.</p>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.html#pandas.Series.plot" title="pandas.Series.plot">Series.plot</a>([kind, ax, figsize, ….])</td>
        <td>Series plotting accessor and method</td>
      </tr>
    </tbody>
  </table>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.area.html#pandas.Series.plot.area" title="pandas.Series.plot.area">Series.plot.area</a>(**kwds)</td>
        <td>Area plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.bar.html#pandas.Series.plot.bar" title="pandas.Series.plot.bar">Series.plot.bar</a>(**kwds)</td>
        <td>Vertical bar plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.barh.html#pandas.Series.plot.barh" title="pandas.Series.plot.barh">Series.plot.barh</a>(**kwds)</td>
        <td>Horizontal bar plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.box.html#pandas.Series.plot.box" title="pandas.Series.plot.box">Series.plot.box</a>(**kwds)</td>
        <td>Boxplot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.density.html#pandas.Series.plot.density" title="pandas.Series.plot.density">Series.plot.density</a>([bw_method, ind])</td>
        <td>Generate Kernel Density Estimate plot using Gaussian kernels.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.hist.html#pandas.Series.plot.hist" title="pandas.Series.plot.hist">Series.plot.hist</a>([bins])</td>
        <td>Histogram.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.kde.html#pandas.Series.plot.kde" title="pandas.Series.plot.kde">Series.plot.kde</a>([bw_method, ind])</td>
        <td>Generate Kernel Density Estimate plot using Gaussian kernels.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.line.html#pandas.Series.plot.line" title="pandas.Series.plot.line">Series.plot.line</a>(**kwds)</td>
        <td>Line plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.pie.html#pandas.Series.plot.pie" title="pandas.Series.plot.pie">Series.plot.pie</a>(**kwds)</td>
        <td>Pie chart.</td>
      </tr>
    </tbody>
  </table>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.hist.html#pandas.Series.hist" title="pandas.Series.hist">Series.hist</a>([by, ax, grid, xlabelsize, …])</td>
        <td>Draw histogram of the input series using matplotlib.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Serialization / IO / Conversion</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_pickle.html#pandas.Series.to_pickle" title="pandas.Series.to_pickle">Series.to_pickle</a>(path[, compression, protocol])</td>
        <td>Pickle (serialize) object to file.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_csv.html#pandas.Series.to_csv" title="pandas.Series.to_csv">Series.to_csv</a>(*args, **kwargs)</td>
        <td>Write object to a comma-separated values (csv) file.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_dict.html#pandas.Series.to_dict" title="pandas.Series.to_dict">Series.to_dict</a>([into])</td>
        <td>Convert Series to {label -&gt; value} dict or dict-like object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_excel.html#pandas.Series.to_excel" title="pandas.Series.to_excel">Series.to_excel</a>(excel_writer[, sheet_name, …])</td>
        <td>Write object to an Excel sheet.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_frame.html#pandas.Series.to_frame" title="pandas.Series.to_frame">Series.to_frame</a>([name])</td>
        <td>Convert Series to DataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_xarray.html#pandas.Series.to_xarray" title="pandas.Series.to_xarray">Series.to_xarray</a>()</td>
        <td>Return an xarray object from the pandas object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_hdf.html#pandas.Series.to_hdf" title="pandas.Series.to_hdf">Series.to_hdf</a>(path_or_buf, key, **kwargs)</td>
        <td>Write the contained data to an HDF5 file using HDFStore.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_sql.html#pandas.Series.to_sql" title="pandas.Series.to_sql">Series.to_sql</a>(name, con[, schema, …])</td>
        <td>Write records stored in a DataFrame to a SQL database.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_msgpack.html#pandas.Series.to_msgpack" title="pandas.Series.to_msgpack">Series.to_msgpack</a>([path_or_buf, encoding])</td>
        <td>Serialize object to input file path using msgpack format.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_json.html#pandas.Series.to_json" title="pandas.Series.to_json">Series.to_json</a>([path_or_buf, orient, …])</td>
        <td>Convert the object to a JSON string.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_sparse.html#pandas.Series.to_sparse" title="pandas.Series.to_sparse">Series.to_sparse</a>([kind, fill_value])</td>
        <td>Convert Series to SparseSeries.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_dense.html#pandas.Series.to_dense" title="pandas.Series.to_dense">Series.to_dense</a>()</td>
        <td>Return dense representation of NDFrame (as opposed to sparse).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_string.html#pandas.Series.to_string" title="pandas.Series.to_string">Series.to_string</a>([buf, na_rep, …])</td>
        <td>Render a string representation of the Series.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_clipboard.html#pandas.Series.to_clipboard" title="pandas.Series.to_clipboard">Series.to_clipboard</a>([excel, sep])</td>
        <td>Copy object to the system clipboard.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.to_latex.html#pandas.Series.to_latex" title="pandas.Series.to_latex">Series.to_latex</a>([buf, columns, col_space, …])</td>
        <td>Render an object to a LaTeX tabular environment table.</td>
      </tr>
    </tbody>
  </table>
</div>
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  <h2>Sparse</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
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    <col width="90%">
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    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.SparseSeries.to_coo.html#pandas.SparseSeries.to_coo" title="pandas.SparseSeries.to_coo">SparseSeries.to_coo</a>([row_levels, …])</td>
        <td>Create a scipy.sparse.coo_matrix from a SparseSeries with MultiIndex.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.SparseSeries.from_coo.html#pandas.SparseSeries.from_coo" title="pandas.SparseSeries.from_coo">SparseSeries.from_coo</a>(A[, dense_index])</td>
        <td>Create a SparseSeries from a scipy.sparse.coo_matrix.</td>
      </tr>
    </tbody>
  </table>
</div>
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